The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow management at international airports. The implementation of this method has shown superior performance to previous methods in terms of reducing errors, delays and associated costs
Receipt date:11/19/2020 acceptance date:10/1/2021 Publishing date:12/31/2021
This work is licensed under a Creative Commons Attribution 4.0 International License.
Human rights are one of the basic concepts of modern and contemporary times, and political thought as the origin of political science and its source of knowledge have impact in this science and its branches
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(( هُوَ الَّذِي بَعَثَ فِي الْأُمِّيِّينَ رَسُولًا مِّنْهُمْ يَتْلُو عَلَيْهِمْ آيَاتِهِ وَيُزَكِّيهِمْ وَيُعَلِّمُهُمُ الْكِتَابَ وَالْحِكْمَةَ وَإِن كَانُوا مِن قَبْلُ لَفِي ضَلَالٍ مُّبِينٍ)) Jumaa verse /38
The topic of the research that is in your hands deals with the
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